October 2020 - Comp-neuro - lists.cnsorg.org

Postdoctoral Swartz Fellowship Positions in Theoretical and Computational Neuroscience at Yale
by Murray, John Oct. 28, 2020

Oct. 28, 2020

Postdoctoral Swartz Fellowship Positions in Theoretical and Computational Neuroscience at Yale University The Swartz Center for Theoretical Neurobiology at Yale University invites applications for up to two postdoctoral positions in Theoretical and Computational Neuroscience, with flexible start date in 2021. Competitive candidates include those with a strong quantitative background who wish to gain neuroscience research experience. We especially encourage candidates with an interest in collaborating directly with experimental neuroscientists. The candidates will be expected to perform theoretical/computational studies relevant to one or more laboratories of the Swartz Center at Yale (for a list of affiliated faculty, see: https://medicine.yale.edu/neuroscience/swartz/corelabs.aspx) and will be encouraged to participate in an expanding quantitative biology environment at Yale. Candidates must hold a Ph.D. or equivalent degree by the time of beginning the fellowship. Please send a CV, selected (p)reprints, contact information for two or three references, and a statement of research interests including which laboratories at Yale are of interest. All application materials should be sent electronically to the following e-mail address: john.murray(a)yale.edu<mailto:john.murray@yale.edu>. Applications will be reviewed as they are received, but priority will be given to those received on or before January 15, 2021. For any questions, please contact John Murray. Yale University is an affirmative action/equal opportunity employer. Yale values diversity in its faculty, students, and staff and especially welcomes applications from women and underrepresented minorities. https://neurojobs.sfn.org/job/27534/postdoctoral-swartz-fellowship-position… John D. Murray ----------------------------------------------- Assistant Professor of Psychiatry, Physics, and Neuroscience Yale University murraylab.yale.edu<http://murraylab.yale.edu/> -----------------------------------------------

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SMILES virtual workshop @ICDL 2020
by Xavier Hinaut Oct. 28, 2020

Oct. 28, 2020

The SMILES (Sensorimotor Interaction, Language and Embodiment of Symbols) Workshop will take place virtually at the ICDL 2020 (International Conference on Developmental Learning). * Call for abstracts and papers: - Deadline: 25th of September 2020 - papers abstracts: 2 pages - long papers: 4-6 pages - Submissions: smiles.conf(a)gmail.com <mailto:smiles.conf@gmail.com> - Papers format: same as ICDL conference https://cis.ieee.org/publications/t-cognitive-and-developmental-systems/tcd… <https://cis.ieee.org/publications/t-cognitive-and-developmental-systems/tcd…> - Workshop dates (coming soon): the days before or after the ICDL conference (26-30 October 2020) * Workshop Short Description On the one hand, models of sensorimotor interaction are embodied in the environment and in the interaction with other agents. On the other hand, recent Deep Learning development of Natural Language Processing (NLP) models allow to capture increasing language complexity (e.g. compositional representations, word embedding, long term dependencies). However, those NLP models are disembodied in the sense that they are learned from static datasets of text or speech. How can we bridge the gap from low-level sensorimotor interaction to high-level compositional symbolic communication? The SMILES workshop will address this issue through -an interdisciplinary approach involving researchers from (but not limited to): - Sensori-motor learning, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Sensori-motor learning, - Symbol grounding and symbol emergence, - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and acquisition in brains and machines, - Models of animal communication, - Understanding composition and temporal processing in neural network models, and - Enaction, active perception, perception-action loop. * More info - contact: smiles.conf(a)gmail.com <mailto:smiles.conf@gmail.com> - organizers: Xavier Hinaut, Clement Moulin-Frier, Silvia Pagliarini, Joni Zhong, Loo CHU KIONG, Michael Spranger, Tadahiro Taniguchi - invited speakers (coming soon) - workshop website (comming soon): https://sites.google.com/view/smiles-workshop/ <https://sites.google.com/view/smiles-workshop/> - ICDL conference website: https://cdstc.gitlab.io/icdl-2020/ <https://cdstc.gitlab.io/icdl-2020/> * Workshop Long Description Recently Deep Learning networks have broken many benchmarks in Natural Language Processing (NLP), e.g. [1]. Such breakthroughs are realized by a few mechanisms (e.g. continuous representations like word embedding, attention mechanism, ...). However, no equivalent finding happened towards the understanding of which mechanisms enable the brain to perform similar functions. Deep Learning does not reproduce learning mechanisms nor the dynamics of the brain. The brain needs to parse incoming stimuli and learn from them incrementally, it cannot unfold time like deep learning algorithms such as Back-propagation through time (BPTT). Thus, we still lack the key neuronal mechanisms needed to properly model the (hierarchies of) functions in language perception and production. Other models of language processing reproducing the behavior of brain dynamics (Event-Related-Potentials (ERPs) [2] or functional Magnetic Resonance Imaging (fMRI) [3]) have been developed. However, such model softens lack explanatory power demonstrating the causes of such observed dynamics: i.e. what is computed and why is it computed – for which purpose? We need more biologically plausible learning mechanisms while producing causal explanations of the experimental data modelled. There is converging evidence that language production and comprehension are not separated processes in a modular mind, they are rather interwoven, and this interweaving is what enables people to predict themselves and each other [4].Interweaving of action and perception is important because it allows a learning agent (or a baby) to learn from its own actions: for instance, by learning the perceptual consequences(e.g. the heard sounds) of its own actions (e.g. vocal productions) during babbling [5]. Thus, the agent learns in a self-supervised way instead of relying only on supervised learning, which in contrast, imply non-biological teacher signals cleverly designed by the modeler. Explicit neuronal models explaining which are the mechanisms shaping these perceptuo-motor units through development are missing. The existence of sensorimotor (i.e. mirror) neurons at abstract representation levels (often called action-perception circuits [6]), jointly with the perceptuo-motor shaping of sensorimotor gestures [5], suggest the existence of similar action-perception mechanisms implemented at different levels of hierarchy. How could we go towards such hierarchical architectures based on action-perception mechanisms? Importantly, a language processing model needs a way to acquire the semantics of the (symbolic) perceptuo-motor gestures and of the more abstract representations, otherwise it would consider only morphosyntactic and prosodic featuresof language. These symbolic gestures, i.e. signs, need to be grounded to the mental concept, i.e. signified, they are representing. Several theories and robotic experiments give examples of how symbols could be grounded or how symbols could emerge [7]. However, current neurocomputational models aiming to explain brain processes are not grounded. Robotics have an important role here for the grounding of semantics by experiencing the world through interactions with the physical world and with humans. We need mechanisms that start from raw sensory perception and raw motor commands in order to let emerge plausible representations through development, instead of arbitrary representations. Finally, computational models of emergent communication in agent populations are currently gaining interest in the machine learning community [8], [9]. These contributions show how a communication system can emerge to solve cooperative tasks in sequential environments. However, they are still relatively disconnected from the earlier theoretical and computational literature aiming at understanding how language might have emerged from a prelinguistic substance [10], [11]. We need to conceive communication as the emergent result of a collective behavior optimization process and to ground the resulting computational models into the theoretical literature from language evolution research. The SMILES workshop will aim at discussing each of the questions mentioned above, together with original approaches on how to integrate them. [1] J. Devlin et al., 2018. [2] H. Brouwer and J. C. J. Hoeks, 2013. [3] M. Garagnani et al. 2008. [4] M. J. Pickering and S. Garrod, 2013. [5] J.-L. Schwartz et al., 2012. [6] F. Pulvermüller and L. Fadiga, 2010. [7] T. Taniguchi et al., 2016. [8] S. Sukhbaatar et al.,2016. [9] I. Mordatch and P. Abbeel, 2017. [10] M. Tomasello et al., 2005. [11] P.-Y. Oudeyer and L. Smith, 2015. Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Université de Bordeaux Institut des Maladies Neurodégénératives +33 5 33 51 48 01 www.xavierhinaut.com

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Scientist I position at the Allen Institute - Bio-realistic Modeling of Reconstructed Cortical Tissue
by Anton Arkhipov Oct. 27, 2020

Oct. 27, 2020

Scientist I - Bio-realistic Modeling of Reconstructed Cortical Tissue https://alleninstitute.hrmdirect.com/employment/job-opening.php?req=1415274 Our mission at the Allen Institute is to advance our understanding of how the brain works in health and disease. Using a team science approach, we strive to discover how the brain implements fundamental computations through the integration of technological innovation, cutting-edge experiments, modeling, and theory. The Allen Institute is seeking exceptional candidates for a BRAIN Initiative-funded position of Scientist in our Seattle-based multidisciplinary organization. The Scientist will join the computational team of Anton Arkhipov and will focus on data analysis and modeling of structure, activity, and computations in mouse cortical circuits. This project will take advantage of unprecedented experimental datasets from the Allen Institute that contain a systematic characterization of synaptic connections between the cell types (https://portal.brain-map.org/explore/connectivity/synaptic-physiology) and a connectome of individual neurons coupled with dense recordings of activity in the mouse visual cortex (https://microns-explorer.org<https://microns-explorer.org/>). The Scientist will work collaboratively with colleagues to integrate these data into new, highly realistic network models of cortical circuits, use the models to explore theoretical predictions, and provide them as a resource to fuel future theoretical, modeling, and experimental work in the community. Our computational team collaborates closely with experimentalists to build systematic classifications of structure and function of the mouse visual cortex based on high-throughput recordings in vitro (e.g., Gouwens et al., Nature Neurosci., 2019; Gouwens et al., Cell, in press, 2020, https://doi.org/10.1101/2020.02.03.932244) and in vivo (e.g., Siegle et al., Nature, in press, 2020, https://doi.org/10.1101/805010) Using systematically constructed models of neurons from diverse types, we are building and simulating data-driven, highly realistic models of the mouse visual cortex (Arkhipov et al., PLOS Comp. Bio., 2018; Billeh et al., Neuron, 2020; https://portal.brain-map.org/explore/models) The team also develops and disseminates modeling software (https://alleninstitute.github.io/bmtk/; https://github.com/AllenInstitute/sonata) Join us to analyze world-class experimental data and build the next generation of brain models! Essential Functions * Collaborate with in-house experimentalists to analyze data from the synaptic physiology and 2-photon calcium imaging/electron microscopy connectomics datasets. * Use these data to build and simulate models of cortical circuits, in order to study mechanisms connecting circuit structure and function. * Publish/present findings in peer-reviewed journals/scientific conferences. Required Education and Experience * PhD degree in Neuroscience, Physics, Applied Mathematics, or related fields. * 0-2 years of post-doctoral experience. * Strong publication record. * Track record of scientific excellence and independent thinking. Preferred Education and Experience * Experience in computational neuroscience and/or systems neuroscience is preferred, but other strong applicants will be considered (with background in computational physics, biophysics, and related disciplines). * Candidates with strong background in experimental systems neuroscience, willing to switch to computational work, are encouraged to apply. * Experience with scientific programming (e.g., in Python) and sharing/collaborative development of software (e.g., GitHub) is a plus. Physical Demands * Fine motor movements in fingers/hands to operate computers and other office equipment; lab equipment Position Type/Expected Hours of Work * This role is currently able to work remotely due to COVID-19 and our focus on employee safety; this may change, and you may be required to work onsite at our South Lake Union office as safety restrictions are lifted in relation to COVID-19. It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities. Apply here: https://alleninstitute.hrmdirect.com/employment/job-opening.php?req=1415274

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New release of the Comp-Neuro Fedora Linux operating system for computational neuroscience is now available for download
by Ankur Sinha Oct. 27, 2020

Oct. 27, 2020

Hello everyone, (Apologies for the cross posts) I am happy to announce that the latest release of the Comp-Neuro Fedora Linux based operating system for computational neuroscience research is now available for download from: https://labs.fedoraproject.org/comp-neuro/ For those that prefer torrents to direct server downloads, it can also be downloaded here: https://torrent.fedoraproject.org/ Detailed documentation can be accessed at: https://neuro.fedoraproject.org Based on the Fedora Workstation OS[1], the Comp-Neuro installer image includes a plethora of computational neuroscience software[2]. This includes: - commonly used simulators: NEST, NEURON, Brian2, Arbor, Auryn, CalC, COPASI, GENESIS, MOOSE; - the complete Python 3.9 science stack: Matplotlib, Jupyter notebooks, Numpy, Pandas, Pillow, Scikit-image, Scikit-learn, Scipy, Statsmodels, Sympy, *and* other utilities such as GNU Octave. Comp-Neuro Fedora also uses the popular and modern GNOME desktop environment[3], and so includes all the productivity tools that are part of the latest GNOME 3.38 release. Further, more software that is not included in the installation media can also be installed from the Fedora software repositories[4] and from FlatHub[5]. The ISO installer image is a "live" image, which means one can also run the operating system directly off the image without installing it to disk Fedora, and so Comp-Neuro Fedora is completely Free and Open Source Software, which is free for everyone to use, share, study, and modify. It is developed by the volunteer community driven NeuroFedora Special Interest Group (SIG). Any feedback and comments are most welcome[6]. If you develop software for neuroscience research, please consider getting in touch with the NeuroFedora community to help us include it in NeuroFedora. Everyone is welcome to join the community and work on whatever tasks they find interesting[7]. No prior knowledge or skills are expected. [1] https://getfedora.org/en/workstation/ [2] https://docs.fedoraproject.org/en-US/neurofedora/compneuro-tools/ [3] https://www.gnome.org/ [4] https://docs.fedoraproject.org/en-US/neurofedora/software/ [5] https://flathub.org/home [6] https://docs.fedoraproject.org/en-US/neurofedora/communicating/ [7] https://docs.fedoraproject.org/en-US/neurofedora/contributing/ On behalf of the NeuroFedora community, -- Thanks, Regards, Ankur Sinha (He / Him / His) | https://ankursinha.in Research Fellow at the Silver Lab, University College London | http://silverlab.org/ Free/Open source community volunteer at the NeuroFedora project | https://neuro.fedoraproject.org Time zone: Europe/London

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Job opportunity - Postdoctoral Sleep Researcher at Bitbrain (Zaragoza, Spain)
by Eduardo López-Larraz Oct. 27, 2020

Oct. 27, 2020

We are looking for a postdoctoral sleep researcher to join Bitbrain <https://www.bitbrain.com/> and work on an EU-funded neurotechnology research project. The main objective will be to exploit some of the most recent advances in sleep research to develop interventions based on cutting-edge wearable neurotechnology for sleep (and sleep-mediated cognitive processes) improvement. The candidate will join Bitbrain <https://www.bitbrain.com/>’s interdisciplinary R&D department of applied neuroscience and neurotechnology and will lead all the R&D activities related to sleep. The candidate will have to: 1) design the R&D strategy of this new area in the company, which will require attending and participating in international events and networks, and 2) design and carry out a feasibility study in sleep improvement using innovative and practical technologies that can be used outside the lab. The position is initially offered for 12 months and includes a relocation and training package. *Requirements*: Sleep expert with a PhD degree in Neuroscience, Psychology, Biomedical Engineering or similar. Strong background in sleep research, understanding of EEG (required) and brain stimulation (desirable). Project management skills. Problem solving and potential of growth. English is required, Spanish is a plus. *We offer*: - Competitive salary. Benefits associated with mobility and family. - Possibility of doing part of the work remotely (to be discussed). - Work-life balance. * Starting date: *01.03.2021 *Application Deadline*: 15.12.2020 More information and application procedure: https://euraxess.ec.europa.eu/jobs/545040

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postdoc position with Christopher Rozell at Georgia Tech
by Christopher Rozell Oct. 27, 2020

Oct. 27, 2020

A postdoctoral position in computational neuroscience is available in the lab of Christopher Rozell at the Georgia Institute of Technology (Atlanta, GA). This BRAIN Initiative research project seeks to advance the field of closed-loop computational neuroscience by pioneering the use of real-time feedback stimulation during experiments to decouple recurrently connected circuit elements and make stronger causal inferences about circuit interactions. This position will have a broad opportunity to develop models and algorithms that are implemented in novel experiments using closed-loop optogenetic stimulation. We aim to provide both new scientific insight about computation in neural circuits (especially sensory coding in the thalamo-cortical circuit) as well as new approaches and algorithmic tools for the community to use in novel electrophysiology experiments. This position will work as part of a team and in close collaboration with the experimental lab of Garrett Stanley (also at Georgia Tech), and it is expected that the computational and algorithmic approaches will be implemented experimentally through close partnership with experimentalists in the Stanley Laboratory. Applicants should hold a PhD in a related discipline with a strong record of research impact, quantitative thinking and collaborative work. Experience in computational neuroscience, machine learning, feedback control, and causal inference is all advantageous. The lab is committed to providing a diverse and inclusive environment for all scholars, and applications are especially encouraged from all underrepresented groups. Additionally, the lab is committed to the professional development of the members, making it valuable preparation for people who are interested in academic, industrial or entrepreneurial careers. The position has no mandatory teaching or administrative duties. Excellent (written and oral) communication skills in English are required. This particular project is part of the Collaborative Research in Computational Neuroscience program (CRCNS), providing access to a community of researchers across the country who are focused on similar types of collaborations between computational and experimental labs. Georgia Tech's campus in the heart of midtown Atlanta, which has a thriving and collaborative neuroscience community that has a particular emphasis on computational and systems neuroscience. Atlanta is also one of the fastest-growing metropolitan areas in the United States, boasting a wide range of opportunities for recreation and culture. Georgia Tech has competitive benefits (including comprehensive medical insurance) and is an equal opportunity employer. The position would ideally start as soon as possible (spring 2021). The appointment is initially for 12 months with the expectation of renewal. Compensation will be commensurate with relevant experience. Candidates should send a CV, a statement of research experience and interests, expected date of availability, and the contact information for three references to crozell(a)gatech.edu with the subject line "CRCNS postdoc". Application review will proceed until the position is filled and should be received by December 1 for full consideration.

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[virtual event] - neuromorphic colloquium
by Chiara Bartolozzi Oct. 26, 2020

Oct. 26, 2020

The NEUROTECH Educational Team is organizing a webinar series on neuromorphic computing technologies. The objective is to offer educational material about the field but also hold discussions with the experts about how the field started, how it evolved, where it’s going and how it’s going to shape the future industrial landscape. The first webinar will be on the 3rd of November at 16 CET and the question of the day is: “What is Neuromorphic Engineering?”. The first speakers are: Prof. Giacomo Indiveri, Prof. Steven Furber, Prof. Bernabé Linares-Barranco and Prof. Kwabena Boahen. You can register for free here: https://neurotech.iniforum.ch/educational/ Join us and spread the word! This initiative is supported as part of the NEUROTECH EU-H2020 coordination and support action. ----------------------------------------------------------------------------------------------------------------------------------------- About Neurotech: Our mission is to catalyse research and collaboration in NCT. Today's neuromorphic community in Europe is leading the state of the art in this domain. The community counts an increasing number of labs that work on theory, modelling, and implementation of neuromorphic computing systems. The NEUROTECH Project will create a Cartography of NCT in Europe, explore Roadmaps for its development, collect educational and information resources on NCT, and inform about upcoming and previous events. https://neurotech.iniforum.ch Follow us on LinkedIN: NEUROTECHAI

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Postdoc position in Bologna
by Andrea Santamaria Oct. 26, 2020

Oct. 26, 2020

Dear Sirs, We are the ERC Project INSCRIBE Invention of Scripts and their Beginnings. Sorry for having forget the title, which I've now included in the object as "Postdoc position in Bologna". We would therefore be delighted to share our announcement on your list. You can find the dame text here below in bold. The ERC Project INSCRIBE Invention of Scripts and their Beginnings, based at the University of Bologna, Italy, seeks candidates for a postdoctoral position in interdisciplinary research with expertise in computational neuroscience. The selected candidate will straddle the borders of neuroscience, cognition and the evolution of graphic codes, to apply quantitative methods to large databases with the goal of establishing commonalities worldwide in the evolution of symbols from a broadly cognitive, and more specifically, motor-driven and visual perspective. The ideal candidate will have earned a PhD in either neuroscience or neural computational sciences, with skills in statistical methods. The position is renewable on a yearly basis, up to three consecutive years and can be held remotely. Deadline: 28 October 2020. For more information on how to apply: https://site.unibo.it/inscribe/en/jobs or contact: s.ferrara(a)unibo.it. Thank you in advance and Kind Regards, Andrea Santamaria Get Outlook for Android<https://aka.ms/ghei36>

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Neuromatch conference Oct 26-30
by Goodman, Daniel F M Oct. 25, 2020

Oct. 25, 2020

This is just a reminder that the Neuromatch conference starts tomorrow (at the time of writing) Oct 26-30. We have around 900 talks on all aspects of neuroscience, debates, panels, as well as special series in partnership with the BRAIN initiative, Black in Neuro, and Queer in Neuro. Check our our website here: https://www.neuromatch.io/ Registration is $25, but can be waived with the press of a button, no questions asked, if you're not able to pay. You can see the full agenda with recommendation engine once you've registered, or you can use our old fashioned schedule here before registering (but no automatic recommendations on this one): https://neural-reckoning.github.io/nmc3_provisional_schedule/ Please pass this message on to anyone or any list you think would be interested. Many thanks, The Neuromatch organisers

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Postdoc position on Biological Deep Learning
by Walter Senn Oct. 23, 2020

Oct. 23, 2020

Dear all A second postdoc position devoted to learning in deep cortical networks is available in our Computational Neuroscience labs at the University of Bern, Switzerland. This position is focussed on formulating error-based learning in deep cortical networks in terms of a principle of least action. We will extend this theory to natural gradient learning and to learning with spiking neurons. The research of our labs is more broadly devoted to biologically realistic models of spatio-temporal processing in cortical networks and their relation to reinforcement learning, Bayesian computing, and neuromorphic implementations. The position is part of the European Human Brain Project and is available by January 1st, 2021, for 2 years (extendable). We offer a stimulating environment with three research groups in theoretical and computational neuroscience, along with experimental neuroscience at the same Department of Physiology (physio.unibe.ch/gruppen.aspx <http://physio.unibe.ch/gruppen.aspx>), as well as close collaborations with other labs in neuroscience, artificial intelligence and neuromorphic engineering. Ideal candidates should have a strong background in computational neuroscience, machine learning, applied mathematics and/or physics. Please send your CV, publication list, letter of motivation and contact information for at least two references to Walter Senn (walter.senn(a)unibe.ch <mailto:walter.senn@unibe.ch>) and Mihai Petrovici (mihai.petrovici(a)unibe.ch <mailto:mihai.petrovici@unibe.ch>), with cc to Virginie Sabado (virginie.sabado(a)unibe.ch <mailto:virginie.sabado@unibe.ch>). The first evaluation round will begin on November 8, 2020. The positions will remain open until filled. With best regards, Mihai Petrovici and Walter

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